One of more difficult problems companies face is deciding where to allocate resources. Decisions are made when new initiatives are considered and, at least in theory, during frequent project reviews. Companies consider researching new technologies, purchasing existing technologies, acquiring small companies, mergers with competitors, line extensions to existing products, repositioning of products in the market, new advertising campaigns, and a host of other tasks. Despite wide differences in product areas, the processes whereby these many projects and initiatives are managed have much in common: evaluate the projects, assess the company's strategy and resources, and allocate these finite resources to the projects so as to maximize estimates of success, minimize estimates of risk or harm, and match the company's strategic goals.
Despite the obvious importance of project portfolio management, it is generally found difficult to do efficiently and correctly. Unlike commodity portfolio management, historical data is of limited utility in predicting the finances and success of new projects. Additionally, the start-up and stop costs of projects are much larger and less-easily quantified, there are more complex probabilistic relationships between projects, and there is much greater need and opportunity for active management of projects than for commodities. For these reasons, the vast array of tools developed for commodities management are of limited utility in project portfolio management. Existing software tends to include a variety of simplistic assumptions and very limited ability to gauge the tradeoffs between different portfolios. Therefore, companies that have seriously considered project management typically use a mixture of qualitative and quantitative project assessment techniques, graphic depictions of project and portfolio characteristics to allow visually setting a “balanced” portfolio, or rough uses of optimization methods and ranking tools. The more common case is that a company has only rough plan for managing projects, poor merging of project manager assessments with executive-level decisions, and a weak appreciation for the limitations of the software and assessment tools it does use. (For example, quantitative assessment tools often mislead managers into trusting numbers that are extremely uncertain.) In almost all cases, the existing tools evaluate projects independently and assume there is no relationship between them.
Accordingly, there is a need for a suite of modular tools that can be easily configured and mixed so as to rapidly devise customized solutions for a company. In particular, there is a need for a variety of means to calculate probabilistic risk/benefit measures of portfolios to perform data visualization tools, to perform group decision-making, to optimize, to perform tradeoff analysis, and to customize simulations of projects and portfolios.